University StudentsAI and security games were introduced to a class ofUniversity of Southern California (USC) freshmen asa two-week unit in their Freshman Academy coursein fall 2015, which is an introductory engineeringcourse aimed at introducing students to ongoingresearch at USC across various engineering disci-plines. Similar to the high school course described inthe previous section, the two-week AI unit portion ofthe course was also designed based on a seminar atUSC titled CS499: Artificial Intelligence and ScienceFiction. Aligning with unit objectives for the highschools students, objectives for the university stu-dents included honing probabilistic reasoning skills,enhancing student interest in AI, and high levels ofstudent satisfaction with the learning experience.

Participants
The 30 students who took part in the AI unit were all
USC freshmen majoring in engineering. Based on a
subset of students who responded to our feedback
survey, the mean age of the group was 18. 2 years, and
roughly 77 percent were female.

Unit StructureInstructors opened the unit by introducing securityas a global concern, and highlighted problems spe-cific to wildlife security. Step by step, the unit intro-duced more complex concepts, starting with basicconcepts in AI and game theory. As part of our scaf-folding framework, to teach the notion of payoffs ina game context, the classic prisoner’s dilemma prob-lem in game theory was introduced. Discussion wasfacilitated around this topic to provide foundationalunderstanding regarding payoffs in the games (thatis, animal densities and penalties). Faculty and CEOsof technical startups then facilitated discussionaround the use of AI applications to solve real-worldsecurity problems, painting a picture of the variousways in which AI can influence day-to-day life. Sim-ilar to the high school students, the unit culminatedwith students integrating and applying their knowl-edge to play the games. Basic game-theoretic con-cepts such as maximin were explained to help stu-dents to focus on subsets of information in decisionmaking: for instance, in the case of maximin, whenonly information about the payoffs in the game isavailable, instructors aimed to help students designthe most conservative strategy.

Final Project
Similar to the final project for high school students
described above, following the lecture and discus-sion-based elements of the unit, students played the
board game. Here, students first played as rangers.
The class was divided into seven groups, each of
which designed its own defender strategy on a game
board. Some groups chose to allocate ranger coverage in proportion to the number of animals, whereas others placed highest coverage at the highest animal density region and uniformly everywhere else;
some others developed strategies in which the
expected value for poachers was nearly zero across all
of the regions of the park. Each group’s strategy was
then shown to the other groups, who played the
game in the poacher role against their peers’ defender strategies.

Results of GamesThe resulting defender utilities for each universitystudent group playing the board games is shown infigure 4. The team with the lowest defender utility(G3) placed very low coverage (< 0.40) in the highestSUMMER 2017 41